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Hybrid N-way Partial Least Squares and Random Forest Model for Brick Tea Identification Based on Excitation–emission Matrix Fluorescence Spectroscopy
Research article (Food and Bioprocess Technology, 2023) · cited 15× · AI/ML
Hybrid N-way Partial Least Squares and Random Forest Model for Brick Tea Identification Based on Excitation–emission Matrix Fluorescence Spectroscopy
Summary
Hybrid N-way Partial Least Squares and Random Forest Model for Brick Tea Identification Based on Excitation–emission Matrix Fluorescence Spectroscopy is a scholarly article[1].
Key Facts
Hybrid N-way Partial Least Squares and Random Forest Model for Brick Tea Identification Based on Excitation–emission Matrix Fluorescence Spectroscopy's instance of is recorded as scholarly article[2].
References
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APA4ort.xyz Knowledge Graph. (2026). Hybrid N-way Partial Least Squares and Random Forest Model for Brick Tea Identification Based on Excitation–emission Matrix Fluorescence Spectroscopy. Retrieved May 24, 2026, from https://4ort.xyz/entity/hybrid-n-way-partial-least-squares-and-random-forest-model-for-brick-tea-identification-based-on-excitationemission-matr
MLA“Hybrid N-way Partial Least Squares and Random Forest Model for Brick Tea Identification Based on Excitation–emission Matrix Fluorescence Spectroscopy.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/hybrid-n-way-partial-least-squares-and-random-forest-model-for-brick-tea-identification-based-on-excitationemission-matr.
BibTeX@misc{4ortxyz_hybrid-n-way-partial-least-squares-and-random-forest-model-for-brick-tea-identification-based-on-excitationemission-matr_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Hybrid N-way Partial Least Squares and Random Forest Model for Brick Tea Identification Based on Excitation–emission Matrix Fluorescence Spectroscopy}}, year = {2026}, url = {https://4ort.xyz/entity/hybrid-n-way-partial-least-squares-and-random-forest-model-for-brick-tea-identification-based-on-excitationemission-matr}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Hybrid N-way Partial Least Squares and Random Forest Model for Brick Tea Identification Based on Excitation–emission Matrix Fluorescence Spectroscopy — https://4ort.xyz/entity/hybrid-n-way-partial-least-squares-and-random-forest-model-for-brick-tea-identification-based-on-excitationemission-matr (retrieved 2026-05-24)
